Abstract: A prediction based engine control system is disclosed. The engine control system may have sensor configured to sense a current engine operation and generate a corresponding signal and a controller in communication with the sensor. The controller may be configured to receive the signal, compare the current engine operation to an allowable range of engine operation, predict a future engine operation based on the signal, and limit current engine operation based on the prediction, even when the current engine operation is within the allowable range of operation.

Abstract: A prediction based engine control system is disclosed. The engine control system may have sensor configured to sense a current engine operation and generate a corresponding signal and a controller in communication with the sensor. The controller may be configured to receive the signal, compare the current engine operation to an allowable range of engine operation, predict a future engine operation based on the signal, and limit current engine operation based on the prediction, even when the current engine operation is within the allowable range of operation.

Abstract: A method is provided for model optimization. The method may include obtaining respective distribution descriptions of a plurality of input parameters to a model indicative of interrelationships between the input parameters and one or more output parameters. The method may also include specifying respective search ranges for the plurality of input parameters and simulating the model to determine a desired set of input parameters based on a zeta statistic of the model. Further, the method may include determining respective desired distributions of the input parameters based on the desired set of input parameters; determining significance levels of the input parameters in interacting with the output parameter based on the simulation and the desired distributions of the input parameters; and presenting the significance levels.

Abstract: A method is provided for supply chain modeling by a supply chain entity within a supply chain. The supply chain may include a plurality of supply chain entities. The method may include establishing a first supply chain model representing interrelationships between an inventory cost of the supply chain entity and supply capacities of the supply chain entity and establishing a second supply chain model based on the first supply chain model. The method may also include providing a plurality of values of the inventory cost to the second supply chain model to generate corresponding plural sets of desired values of the supply capacities and selecting a set of desired values of the supply capacities from the plural sets of desired values.

Abstract: A method is provided for a virtual sensor system. The method may include establishing a first process model indicative of interrelationships between a plurality of input parameters and a plurality of output parameters and establishing a second process model indicative of interrelationships between at least the plurality of input parameters and modeling errors of the first process model. The method may also include operating the first process model to generate values of the plurality of output parameters and simultaneously operating the second model to generate estimated deviations between the values of the plurality of output parameters and desired values of the plurality of output parameters. Further, the method may include compensating the values of the plurality of output parameters with the estimated deviations to generate the desired values of the plurality of output parameters.

Abstract: A method is provided for a medical risk stratification system. The method may include establishing a medical risk process model indicative of interrelationships between a plurality of medical risks and a plurality of health parameters and obtaining a set of values corresponding to the plurality of health parameters. The method may also include calculating the values of the plurality of medical risks simultaneously based upon the set of values corresponding to the plurality of health parameters and the medical risk process model and presenting the values of the plurality of medical risks.

Abstract: A method is provided for supply chain modeling by a supply chain entity within a supply chain including a plurality of supply chain entities. The method may include obtaining an order fulfillment requirement for a product from a downstream supply chain entity and identifying one or more representative subsystems of the product. The method may also include determining a supply capacity and an inventory requirement for the supply chain entity with respect to the one or more representative subsystems and calculating an inventory cost for the supply chain entity based on the inventory requirement with respect to the one or more representative subsystems.

Abstract: A method is provided for a credit risk profiling system. The method may include establishing a credit risk process model indicative of interrelationships between one or more credit risks and a plurality of financial parameters and obtaining a set of values corresponding to the plurality of financial parameters. The method may also include calculating the values of the one or more credit risks simultaneously based upon the set of values corresponding to the plurality of financial parameters and the credit risk process model, presenting the values of the one or more credit risks, and simultaneously presenting financial return information.

Abstract: A method is provided for a product cost modeling system. The method may include establishing a product cost process model indicative of interrelationships between product costs of one or more existing products and a respective plurality of characteristic parameters of the existing products. The method may also include obtaining a set of values corresponding to a plurality of characteristic parameters of a target product from a data source and calculating the product cost of the target product based upon the set of values corresponding to the plurality of characteristic parameters of the target product and the product cost process model.

Abstract: A method is provided for a virtual sensor system. The method may include establishing a virtual sensor process model indicative of interrelationships between a plurality of sensing parameters and a plurality of measured parameters, and obtaining a set of values corresponding to the plurality of measured parameters. The method may also include calculating the values of the plurality of sensing parameters simultaneously based upon the set of values corresponding to the plurality of measured parameters and the virtual sensor process model, and providing the values of the plurality of sensing parameters to a control system.

Abstract: A method is provided for a medical risk stratification system. The method may include obtaining data records associated with one or more health variables and a plurality of medical risks from a plurality of MRS models based on an expert knowledge combination process and establishing a medical risk process model indicative of interrelationships between the plurality of medical risks and a plurality of health parameters based on the data records. The method may also include obtaining a set of values corresponding to the plurality of health parameters and calculating values of the plurality of medical risks simultaneously based upon the set of values corresponding to the plurality of health parameters and the medical risk process model. Further, the method may include optimizing the plurality of health parameters to minimize the plurality of medical risks simultaneously and presenting the values of the plurality of medical risks.

Abstract: A method is provided for process modeling. The method may include obtaining batch statistics data records associated with one or more input variables and one or more output parameters and selecting one or more input parameters from the one or more input variables. The method may also include generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records and determining desired respective statistical distributions of the input parameters of the computational model.

Abstract: A computer-implemented method to provide a desired variable subset. The method may include obtaining a set of data records corresponding a plurality of variables and defining the data records as normal data or abnormal data based on predetermined criteria. The method may also include initializing a genetic algorithm with a subset of variables from the plurality of variables and calculating Mahalanobis distances of the normal data and the abnormal data based on the subset of variables. Further, the method may include identifying a desired subset of the plurality of variables by performing the genetic algorithm based on the Mahalanobis distances.

Abstract: A method for diagnosing a system is provided. The method may include obtaining a plurality of input parameters from the system. The system may generate actual values of one or more output parameters based on the plurality of input parameters. The method may also include independently deriving values of the one or more output parameters, based on the plurality of input parameters, using a computational model, and detecting a divergence between the derived values and the actual values. Further, the method may include identifying respective desired statistic distributions of the plurality of input parameters, based on the actual values of the one or more output parameters, using the computational model.

Abstract: A computer-implemented method is provided for model optimization. The method may include obtaining respective distribution descriptions of a plurality of input parameters to a model and specifying respective search ranges for the plurality of input parameters. The method may also include simulating the model to determine a desired set of input parameters based on a zeta statistic of the model and determining respective desired distributions of the input parameters based on the desired set of input parameters.

Abstract: A method is provided for a control system. The method may include obtaining data records associated one or more input variables and one or more output parameters, and selecting one or more input parameters from the one or more input variables. The method may also include generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records, and determining desired respective statistical distributions of the one or more input parameters of the computational model.

Abstract: A method for designing a product includes obtaining data records relating to one or more input variables and one or more output parameters associated with the product. One or more input parameters may be selected from the one or more input variables, and a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records may be generated. The method further includes providing a set of constraints to the computational model representative of a compliance state for the product and using the computational model to generate statistical distributions for the one or more input parameters and the one or more output parameters, based on the set of constraints, that represent a design for the product.

Abstract: A computer-implemented method is provided for monitoring model performance. The method may include obtaining configuration information and obtaining operational information about a computational model and a system being modeled. The computational model and the system may include a plurality of input parameters and one or more output parameters. The system may generate respective actual values of the one or more output parameters, and the computational model may predict respective values of the one or more output parameters. The method may also include applying an evaluation rule from a rule set, based on the configuration information, to the operational information to determine whether the rule is satisfied.

Abstract: A computer system for probabilistic modeling includes a display and one or more input devices. A processor may be configured to execute instructions for generating at least one view representative of a probabilistic model and providing the at least one view to the display. The instructions may also include receiving data through the one or more input devices, running a simulation of the probabilistic model based on the data, and generating a model output including a predicted probability distribution associated with each of one or more output parameters of the probabilistic model. The model output may be provided to the display.

Abstract: The present invention includes a system and method configured to analyze a performance of a product. The product has associated process and performance characteristics. The method includes the steps of establishing a plurality of process characteristics associated with the product, establishing an analysis relationship between the process characteristics and the performance characteristic, and analyzing the performance characteristic of the product in response to the relationship.